Surgical Treatment of Cervical Radiculopathy
Bibliographic record
Abstract
STUDY DESIGN: Meta-analysis of published randomized controlled trials (RCTs). OBJECTIVE: To determine whether anterior cervical discectomy and fusion (ACDF), cervical disc replacement (CDR), or minimally invasive posterior cervical foraminotomy (MI-PCF) provides the best outcomes for patients with symptomatic single-level, single-side, and cervical radiculopathy. SUMMARY OF BACKGROUND DATA: The surgical treatment of cervical radiculopathy is still controversial. ACDF has been widely used as a "gold standard." CDR has evolved and become a motion-preserving alternative with a potentially lower incidence of adjacent segment disease. However, both techniques require anterior neck dissection that carries a potential for serious morbidity. MI-PCF is a motion-preserving technique that can be performed with minimal invasiveness but has not gained universal acceptance. METHODS: Electronic database search for RCTs comparing the efficacy and effectiveness of ACDF, CDR, and MI-PCF was performed. Meta-analysis was done for secondary surgical procedures and adverse events. RESULTS: A total of 358 studies were retrieved, of which four RCT reports met the inclusion criteria for this study. Three studies present clinical data comparing ACDF and CDR, and one study presents data comparing ACDF and MI-PCF. Available data from the RCTs analyzed concluded that ACDF, CDR, and MI-PCF result in significant improvements in relevant symptoms, clinical, and functional outcomes in patients with single-level, single side cervical radiculopathy refractory to nonoperative treatment. CDR had the lowest percentage of secondary surgical procedures (P = 0.0178) whereas MICPF had the lowest percentage of adverse events (P < 0.0001). CONCLUSION: All three techniques are effective in treating cervical radicular symptoms. MI-PCF has the lowest rate of adverse events whereas CDR has the lowest rate of secondary procedures. There is insufficient evidence to show which technique is the most effective and provides the longest-lasting symptom relief. LEVEL OF EVIDENCE: 1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".